CSR: Small: RF-Wear: Enabling RF Sensing on Wearable Devices for Non-Intrusive Human Activity, Vital Sign and Context Monitoring
CSR:小型:RF-Wear:在可穿戴设备上实现射频感应,以实现非侵入式人类活动、生命体征和环境监测
基本信息
- 批准号:1617627
- 负责人:
- 金额:$ 49.63万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2016
- 资助国家:美国
- 起止时间:2016-08-01 至 2020-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Wearable devices are growing in popularity at a tremendous rate. Today, millions of people wear fitness trackers and smart watches on a daily basis to track steps, heart rates and sleep. However, the constraints of the built-in sensors in existing wearable devices act as key bottlenecks that limit the broader impact of wearable devices. In particular, accelerometers and gyroscopes can only sense motion and rotation of body parts to which they are attached. Microphones and cameras can capture rich information but come with severe privacy concerns. Many physiological sensors such as respiration and electrocardiogram sensors are intrusive in that they must be placed at certain body locations and require tight skin contact to function. This project focuses on pushing the boundaries of wearable devices by exploring wireless radio as a new sensing modality on wearable devices for human physical activity, vital sign, and context sensing. Compared to existing sensing modalities in wearable devices, radio provides a contactless and privacy-preserving approach to capture rich information about users and their context. The underpinning principle is that movements of different parts of human body caused by different human activities (physical, physiological and contextual) generate different changes on radio signals. By analyzing these changes, the activity that causes the changes can be recognized. Based on this principle, this project aims to pursue five tightly coupled research tasks associated with the goal of exploring radio based sensing on wearable devices: (1) investigating radio as a whole-body motion sensor for recognizing activities of daily living (ADLs); (2) investigating radio as a contact-less physiological sensor for monitoring vital signs; (3) investigating radio as a context sensor for identifying the object a user is interacting with; (4) putting everything together to use a single radio sensing modality for recognizing ADLs, monitoring vital signs, and identifying context simultaneously; and (5) developing power-aware schemes to minimize the power consumption of the wearable device.This project will advance the knowledge and understanding of radio based sensing on wearable devices. It has the potential to fundamentally transform wearable devices as they are currently known. If successful, this project will not only make a theoretical contribution to radio based sensing on wearable devices but also yield a prototype platform, opening up a new world of applications in domains such as healthcare, entertainment, social computing and education.
可穿戴设备正在以惊人的速度普及。如今,数百万人每天都佩戴健身追踪器和智能手表来跟踪步数、心率和睡眠。然而,现有可穿戴设备中内置传感器的限制成为限制可穿戴设备更广泛影响的关键瓶颈。特别地,加速度计和陀螺仪只能感测它们所附接的身体部位的运动和旋转。麦克风和摄像头可以捕捉丰富的信息,但也会带来严重的隐私问题。许多生理传感器(诸如呼吸和心电图传感器)是侵入式的,因为它们必须放置在某些身体位置处并且需要紧密的皮肤接触才能起作用。该项目的重点是通过探索无线电作为可穿戴设备上人类身体活动,生命体征和上下文感知的新传感模式来推动可穿戴设备的边界。与可穿戴设备中现有的传感模式相比,无线电提供了一种非接触和隐私保护的方法来捕获有关用户及其上下文的丰富信息。其基本原理是,人体不同部位的运动由不同的人类活动(身体,生理和环境)引起,对无线电信号产生不同的变化。通过分析这些变化,可以识别导致变化的活动。基于这一原则,本项目旨在开展五项紧密耦合的研究任务,以探索可穿戴设备上基于无线电的传感:(1)研究无线电作为全身运动传感器用于识别日常生活活动(ADL);(2)研究无线电作为非接触式生理传感器用于监测生命体征;(3)研究无线电作为非接触式生理传感器用于监测生命体征。(3)研究无线电作为用于识别用户正在与之交互的对象的背景传感器;(4)将所有东西放在一起以使用单个无线电感测模态来同时识别ADL、监测生命体征和识别背景;以及(5)开发功耗感知方案,以最大限度地降低可穿戴设备的功耗。本项目将促进对可穿戴设备上基于无线电的传感的认识和理解。它有可能从根本上改变目前已知的可穿戴设备。如果成功,该项目不仅将为可穿戴设备上基于无线电的传感做出理论贡献,还将产生一个原型平台,在医疗保健、娱乐、社交计算和教育等领域开辟一个新的应用世界。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Mi Zhang其他文献
Theoretical Derivation and Verification of Liquid Viscosity and Density Measurements Using Quartz Tuning Fork Sensor
使用石英音叉传感器测量液体粘度和密度的理论推导和验证
- DOI:
10.1109/spawda.2019.8681835 - 发表时间:
2019 - 期刊:
- 影响因子:0
- 作者:
Mi Zhang;Dehua Chen;Xiuming Wang - 通讯作者:
Xiuming Wang
Attention-Guided Multi-Scale Segmentation Neural Network for Interactive Extraction of Region Objects from High-Resolution Satellite Imagery
用于从高分辨率卫星图像中交互式提取区域对象的注意力引导多尺度分割神经网络
- DOI:
10.3390/rs12050789 - 发表时间:
2020-03 - 期刊:
- 影响因子:5
- 作者:
Kun Li;Xiangyun Hu;Huiwei Jiang;Zhen Shu;Mi Zhang - 通讯作者:
Mi Zhang
A Heterostructure-In-Built Multichambered Host Architecture Enabled by Topochemical Self-Nitridation for Rechargeable Lithiated Silicon-Polysulfide Full Battery
一种通过拓扑化学自氮化实现的异质结构内置多室主机架构,用于可充电锂化硅多硫化物全电池
- DOI:
10.1002/adfm.202103456 - 发表时间:
2021 - 期刊:
- 影响因子:19
- 作者:
Yunhong Wei;Mi Zhang;Li Yuan;Boya Wang;Hongmei Wang;Qian Wang;Yun Zhang;Junling Guo;Hao Wu - 通讯作者:
Hao Wu
Enhancing Time Series Predictors with Generalized Extreme Value Loss
通过广义极值损失增强时间序列预测器
- DOI:
10.1109/tkde.2021.3108831 - 发表时间:
2022 - 期刊:
- 影响因子:8.9
- 作者:
Mi Zhang;Daizong Ding;Xudong Pan;Min Yang - 通讯作者:
Min Yang
Communication Challenges in the IoT
物联网中的通信挑战
- DOI:
10.1109/mprv.2019.2899280 - 发表时间:
2019 - 期刊:
- 影响因子:0
- 作者:
Mi Zhang;X. Jiang;Steve Hodges - 通讯作者:
Steve Hodges
Mi Zhang的其他文献
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{{ truncateString('Mi Zhang', 18)}}的其他基金
Collaborative Research: NeTS: Medium: Towards High-Performing LoRa with Embedded Intelligence on the Edge
协作研究:NeTS:中:利用边缘嵌入式智能实现高性能 LoRa
- 批准号:
2312675 - 财政年份:2023
- 资助金额:
$ 49.63万 - 项目类别:
Standard Grant
NSF Student Travel Grant for 2017 ACM International Conference on Mobile Systems, Applications, and Services (ACM MobiSys)
2017 年 ACM 国际移动系统、应用程序和服务会议 (ACM MobiSys) 的 NSF 学生旅费补助金
- 批准号:
1724807 - 财政年份:2017
- 资助金额:
$ 49.63万 - 项目类别:
Standard Grant
PFI:BIC: iSee - Intelligent Mobile Behavior Monitoring and Depression Analytics Service for College Counseling Decision Support
PFI:BIC:iSee - 用于大学咨询决策支持的智能移动行为监测和抑郁分析服务
- 批准号:
1632051 - 财政年份:2016
- 资助金额:
$ 49.63万 - 项目类别:
Standard Grant
CRII: CHS: WiFi-Based Human Behavior Sensing and Recognition System for Aging in Place
CRII:CHS:基于 WiFi 的人类行为感知和识别系统,用于就地养老
- 批准号:
1565604 - 财政年份:2016
- 资助金额:
$ 49.63万 - 项目类别:
Continuing Grant
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